jlibman / a7-collaborative-coding Goto Github PK

Similarly to your first charting file, you'll write another function (in another file) that accepts a dataset as a parameter and returns a chart.

Once you've completed your project, create a gh-pages branch so that our final product can be posted on the web. Here's the syntax you'll want to use in your terminal:

# Get into your repository
cd YOUR-DIRECTORY-NAME

# Add and commit changes to your current (master) branch
git add .
git commit -m "Commit message goes in here"

# Create and checkout a new branch called 'gh-pages'
git checkout -b gh-pages

# Push all changes (including your new branch) up to GitHub
git push --all
`You should now see your index.html file up on the web at 'your-username.github.io/a5-github-report'.

The first file you should save in your scripts/ directory should contain a function that takes in a dataset as a parameter, and returns a list of information about it. For example:

A function that takes in a dataset and returns a list of info about it: info_function <- function(dataset) { ret <- list() ret$length <- length(dataset) # do some more interesting stuff return (ret) }
We don't expect you to write a generalizable function that detects rows/columns and asks questions of your dataset. Instead, think of this like a simple analysis you would do on this particular dataset, just wrapped in a function. This will allow you to pass your dataset into this function from your index.Rmd file.

Your index.Rmd file will be used to actually generate your report. However, it needs the functions written in other files in order to work (see below). To read in a function you've written in another file, you can use the source function. This is similar to using the library function, but with a file that you've written:

Read in functions from another file:
source("scripts/FILE-NAME.R")
In the Markdown document created, you should leverage the functions written in the other files to do the following:

Write a short summary paragraph that includes information calculated by your summary information function
Render your first chart
Render your second chart
In order to render those charts, you'll need to read in your data in your Readme.md file, and pass your data to those functions. You can read in the file from it's location in the repository (you don't need to copy the file to your repo):

Note, this have been moved to a public repo so you can read it without an access token:
data <- read.csv("https://raw.githubusercontent.com/INFO-498F/a7-survey-data/master/intro_survey_data.csv")
If it isn't clear how to these pieces fit together, reach out to your TA.

In your second .R file, you should write a function that takes in a dataset as a parameter, and returns a visualization of that data. This will allow you to call your charting function from your index.Rmd file, keeping your code much easier to read.